Prostate cancer is the most common cancer type in men worldwide, with approximately 500 new cases in Cyprus each year. High dose rate brachytherapy (HDR-BT) is gaining considerable popularity as a treatment option, due to its high survival rates and its overall minimal disruption in patients’ life. It involves the implantation of catheter needles into pre-planned locations in the patient’s prostate, through which radioactive sources are delivered to the tumour site. Nevertheless, as the needle punctures and penetrates the prostate it imposes substantial deformation on the tissue, often leading to discrepancies between the pre-planned and actual position. Needle misplacement might impact the radiation that can reach the tumour site, causing a deterioration in treatment efficiency. However, in silico models can provide non-invasive alternatives for enhancing the precision during needle placement in HDR-BT, by simulating needle insertion while accounting for the induced tissue deformation.
In our project, CancerMoDeration, we develop a data-driven in silico modelling framework that aims to offer physiologically accurate predictions of needle insertion on a patient-specific basis. Our ambitious objective is to deliver a digital tool with high potential for clinical translation, capable of assisting in the pre-operative planning of HDR-BT and support intra-operative guidance. Our models will be built using pertinent image data from prostate cancer patients undergoing HDR-BT, acquired at the German Oncology Centre (GOC).